灰色模型和线性回归耦合模型在区域护理人力资源预测中的应用

Application of grey model （1, 1 ）-linear regression coupling model in the prediction of regional nursing human resource

目的 以每千人口护士人数预测为例,探讨灰色GM（1,1）和线性回归耦合模型在区域卫生人力资源预测中的应用,提供卫生人力预测方法学参考.方法采用EXCEL公式编程建立灰色GM（1,1）预测模型对每千人口护士数影响因素进行预测,将影响因素预测值代入回归方程对区域护理人力资源进行目标年预测拟合分析.结果运用灰色GM（1,1）和线性回归耦合模型对区域护理人力资源进行预测,其预测值与实际值拟合误差较小,耦合模型预测精度等级为优秀,其预测结果可作为目标年的参考.结论耦合模型弥补了灰色系统模型中不含线性因素的不足,又改善了线性回归预测模型中不能表达指数增长的缺陷,模型构建合理可行.

 Objective Taking the prediction of the number of nurses per thousand cases as an example, to discuss the application of grey model GM（1, 1）-linear regression Coupling Model in the prediction of regional nursing human resource, so as to provide methodology reference for health human resource prediction.Methods The grey model GM （1, 1） was built up by EXCEL formula to predict the influencing factors of the number of nurses per thousand people. The predictive value of the influencing factors were substituted into the regression equation for the annual prediction of regional nursing human resource. Results The fitting error between predicted value and actual value was small when using the grey model GM （1, 1）-linear regression coupling model in the prediction of regional nursing human resource. The accuracy level of this coupling model prediction is excellent, and the prediction result can be used as a reference for target year. Conclusions The coupling model not only makes up for the lack of 1inear factors in the grey system model, but also improves the defect that exponential growth cannot be expressed in the linear regression prediction model, so the construction of the coupling model is reasonable and feasible.